Body size affects the strength of social interactions and spatial organization of a schooling fish (Pseudomugil signifer).

Maksym Romenskyy,Ashley J W Ward,David J T Sumpter,James E Herbert-Read

doi:10.1098/rsos.161056

Maksym Romenskyy, Ashley J W Ward + Show 2 more

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https://doi.org/10.1098/rsos.161056

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Abstract

While a rich variety of self-propelled particle models propose to explain the collective motion of fish and other animals, rigorous statistical comparison between models and data remains a challenge. Plausible models should be flexible enough to capture changes in the collective behaviour of animal groups at their different developmental stages and group sizes. Here, we analyse the statistical properties of schooling fish (Pseudomugil signifer) through a combination of experiments and simulations. We make novel use of a Boltzmann inversion method, usually applied in molecular dynamics, to identify the effective potential of the mean force of fish interactions. Specifically, we show that larger fish have a larger repulsion zone, but stronger attraction, resulting in greater alignment in their collective motion. We model the collective dynamics of schools using a self-propelled particle model, modified to include varying particle speed and a local repulsion rule. We demonstrate that the statistical properties of the fish schools are reproduced by our model, thereby capturing a number of features of the behaviour and development of schooling fish.

Highlights

In sufficiently large collective systems, the behaviour of an individual can be dominated by the generic statistical effects of many individuals interacting, rather than its own behaviour [1]
We investigated the nature of the interactions between the fish using statistical mechanics
We found the inclusion of the attraction rule unnecessary since a combination of fish–fish alignment and fish–wall interactions proved to be sufficient to reproduce the dynamics observed in experiments both statistically and visually [44]

Summary

Introduction

In sufficiently large collective systems, the behaviour of an individual can be dominated by the generic statistical effects of many individuals interacting, rather than its own behaviour [1]. Other experiments with artificial particles have looked for similarities and differences between self-organized living matter and thermal equilibrium systems [15]. These latter approaches gather statistical information about self-organizing structures in order to parametrize models (see, for example, the maximum entropy approach [11,16]). None of these have explicitly solved the inverse problem of using the macro-level properties of animal groups to find out how the individuals within them interact

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